New Finger Biometric Method Using Near Infrared Imaging

Abstract

In this paper, we propose a new finger biometric method. Infrared finger images are first captured, and then feature extraction is performed using a modified Gaussian high-pass filter through binarization, local binary pattern (LBP), and local derivative pattern (LDP) methods. Infrared finger images include the multimodal features of finger veins and finger geometries. Instead of extracting each feature using different methods, the modified Gaussian high-pass filter is fully convolved. Therefore, the extracted binary patterns of finger images include the multimodal features of veins and finger geometries. Experimental results show that the proposed method has an error rate of 0.13%.

Keywords

• finger recognition
• finger vein
• finger geometry
• modified Gaussian high-pass filter
• binarization
• local binary pattern
• local derivative pattern